Question: (Closed) differential expression analysis
0
gravatar for rhasanvandj
3 months ago by
rhasanvandj20
rhasanvandj20 wrote:

Hello

For differential expression analysis, I want to use RSEM-log2 transformed data. With edgeR and DESeq2 this is not possible because log2 transformation created negative values and these packages cannot deal with negative values. log2 transformation of to normalize data.

How should I do differential expression analysis now? Thanks

rna-seq gene • 221 views
ADD COMMENTlink modified 3 months ago by swbarnes29.1k • written 3 months ago by rhasanvandj20
1

Hi,

If your goal is differential expression analysis, you can use RSEM expected counts with edgeR and DESeq2.

ADD REPLYlink written 3 months ago by andres.firrincieli1.0k

This is the other logical option, if gene length has been retained (it can be calculated manually, though). You would have to transform the data back to the unlogged scale, too.

ADD REPLYlink written 3 months ago by Kevin Blighe67k

Hi Kevin Thank you. Do you mean limma and eBayes can work with negative values of log2 transformed dsata?

ADD REPLYlink written 3 months ago by rhasanvandj20

Why are you avoiding the standard DESeq2 or edgeR pipelines which use raw counts? Why do you need to log them first yourself?

ADD REPLYlink written 3 months ago by swbarnes29.1k

Hi Swbarnes2 The reason that I do not use raw count is that my supervisor asked me to use standard data that is normal. He did not accept what I did with raw data. He says use RSEM log transformed because that is normal.

I am really confused about what is correct way.

ADD REPLYlink written 3 months ago by rhasanvandj20

Please show this to your supervisor: https://support.bioconductor.org/p/90672/#90678

ADD REPLYlink written 3 months ago by Kevin Blighe67k

Hello rhasanvandj.

Please do not create duplicate posts: RNAseq Variance calculation

ADD REPLYlink modified 3 months ago • written 3 months ago by Kevin Blighe67k
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